The code works. That was never the question. Paste any public GitHub repo and get its Production Drift Ratio (PDR) in seconds: one number for how far it sits from production-ready, plus a drift history where every point is a real scan, not an estimate. No signup, nothing to install. Deterministic rules, no LLM in the loop, no tokens burned. Nine dimensions, every finding traced to a file and a line. Try it on something vibe-coded and watch the score climb. From the team at ReWeaver AI.
Hey Product Hunt 👋
I use AI coding assistants every day and they're great at the happy path. What kept tripping me up was everything they leave behind. I decided to look at the code. Yeah, I'm that guy.
I found design tokens that don't exist in the design system. Accessibility patterns quietly dropped. Business logic leaking into the presentation layer. Tests that pass the day they're written and protect nothing after.
It doesn't necessarily break the build. It just turns into someone's problem three sprints later.
Most of the tools I looked at answer this by pointing a second LLM at the diff and asking it to guess what the first one missed. You can't audit a guess, and you're paying per token to get one.
DriftDetector measures instead. Scan the same commit twice, you get the same answer. That's what makes the number safe to put in front of a team lead.
The screenshots undersell one thing. The history isn't a chart of a single scan. Every point on it is a real scan of that commit, and you can zoom into any stretch to have that period re-scanned in detail. So you can find the week the drift actually entered, then open that commit on GitHub straight from the table.
Go run it on something you've shipped. Takes seconds, no account, link's at the top. Then post your score here, because I want to see who has the cleanest and the messiest codebase on Product Hunt today. Or drop a repo link and I'll scan it for you and reply, all day.
Two things I'd love your take on:
1. What compliance or architectural packs are missing for your stack?
2. How close does the effort estimate land to your team's real sprint velocity?
— Jonathan, ReWeaver AI
About ReWeaver AI DriftDetector on Product Hunt
“Drift score for any GitHub repo”
ReWeaver AI DriftDetector launched on Product Hunt on August 26th, 2026 and earned 67 upvotes and 1 comments, placing #27 on the daily leaderboard. The code works. That was never the question. Paste any public GitHub repo and get its Production Drift Ratio (PDR) in seconds: one number for how far it sits from production-ready, plus a drift history where every point is a real scan, not an estimate. No signup, nothing to install. Deterministic rules, no LLM in the loop, no tokens burned. Nine dimensions, every finding traced to a file and a line. Try it on something vibe-coded and watch the score climb. From the team at ReWeaver AI.
On the analytics side, ReWeaver AI DriftDetector competes within Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how ReWeaver AI DriftDetector performed against the three products that launched closest to it on the same day.
Who hunted ReWeaver AI DriftDetector?
ReWeaver AI DriftDetector was hunted by Jonathan Gordon. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of ReWeaver AI DriftDetector including community comment highlights and product details, visit the product overview.
Jonathan Gordon